from spacy.lang.en import English
from spacy.util import fix_random_seed


def test_issue5551():
    """Test that after fixing the random seed, the results of the pipeline are truly identical"""
    component = "textcat"
    pipe_cfg = {
        "model": {
            "@architectures": "spacy.TextCatBOW.v1",
            "exclusive_classes": True,
            "ngram_size": 2,
            "no_output_layer": False,
        }
    }

    results = []
    for i in range(3):
        fix_random_seed(0)
        nlp = English()
        example = (
            "Once hot, form ping-pong-ball-sized balls of the mixture, each weighing roughly 25 g.",
            {"cats": {"Labe1": 1.0, "Label2": 0.0, "Label3": 0.0}},
        )
        pipe = nlp.add_pipe(component, config=pipe_cfg, last=True)
        for label in set(example[1]["cats"]):
            pipe.add_label(label)
        nlp.begin_training()

        # Store the result of each iteration
        result = pipe.model.predict([nlp.make_doc(example[0])])
        results.append(list(result[0]))

    # All results should be the same because of the fixed seed
    assert len(results) == 3
    assert results[0] == results[1]
    assert results[0] == results[2]